Fracture detection using land 3D seismic data from the Yellow River Delta, China

Abstract

Over the past 10 years, there has been a consistent increase in using 3D P-wave data to characterize fractures, which is critical for ensuring economic oil and gas production in tight formations of otherwise low permeability. Here, we present a case study of fracture detection using 3D P-wave seismic data from the Yellow River Delta in East China. The target formation is a naturally fractured mud-rock reservoir. The field site has been in production for more than 10 years; however, virgin pressure wells are still being drilled. The purpose of the survey was the remote identification, for future well planning, of zones of high fracture density that are residual oil-charged. A major aspect of this study is to compare the different seismic attributes and different analysis techniques on a common data set for fracture detection. Our aim is to understand the merits of these different techniques, and to establish some basic guidelines for fracture detection using P-wave data. If we assume the fracture population consists of predominantly one major orientation, the azimuthal variation of P-wave seismic attributes, such as traveltime, stacking velocity, reflected wave amplitudes, impedance, etc. can be approximately described by an ellipse. The long axis of the ellipse indicates the fracture orientation, and the relative ratio of the long to short axes of this ellipse is proportional to the fracture density or intensity of the rock concerned. As we know, at least three data points are required to define an ellipse in azimuthal planes. Thus fracture orientation and intensity maps can be built from 3D P-wave data if there is sufficient azimuthal coverage. We shall call this technique azimuthal attribute analysis or the 3A technique. In the practical application of the 3A technique, two methods are often employed to extract the fracture information: full-azimuth surface fitting and narrow-azimuth …